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The Minimum Code Length for Clustering Using the Gray Code
Published on 2011-10-032529 Views
We propose new approaches to exploit compression algorithms for clustering numerical data. Our first contribution is to design a measure that can score the quality of a given clustering result under t
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Presentation
The Minimum Code Length for Clustering Using the Gray Code00:00
Contributions00:01
Demonstration (Synthetic Dataset)01:07
G-COOL01:17
K-means01:32
Results (Real datasets) - 101:43
Results (Real datasets) - 202:01
Outline (1)02:34
Outline (2)02:36
Clustering Focusing on Compression02:40
Our Strategy (1)03:56
Our Strategy (2)04:20
Outline (3)05:35
MCL (Minimum Code Length) - 105:46
MCL (Minimum Code Length) - 206:05
Binary Encoding06:37
MCL with Binary Encoding (1)07:10
MCL with Binary Encoding (2)07:19
MCL with Binary Encoding (3)07:24
MCL with Binary Encoding (4)07:34
MCL with Binary Encoding (5)07:44
MCL with Binary Encoding (6)08:02
MCL with Binary Encoding (7)08:07
MCL with Binary Encoding (8)08:14
MCL with Binary Encoding (9)08:19
MCL with Binary Encoding (10)08:24
Definition of MCL08:47
Minimizing MCL and Clustering08:53
Outline (4)09:21
Optimization by COOL09:28
COOL with Binary Encoding (1)09:58
COOL with Binary Encoding (2)10:12
COOL with Binary Encoding (3)10:19
COOL with Binary Encoding (4)10:36
COOL with Binary Encoding (5)11:02
COOL with Binary Encoding (6)11:09
COOL with Binary Encoding (7)11:21
COOL with Binary Encoding (8)11:24
Noise Filtering by COOL (1)11:30
Noise Filtering by COOL (2)11:51
Algorithm of COOL11:57
Outline (5)12:01
Gray Code12:07
Gray Code Embedding12:53
COOL with Gray Code (G-COOL) - 113:23
COOL with Gray Code (G-COOL) - 213:30
COOL with Gray Code (G-COOL) - 313:45
COOL with Gray Code (G-COOL) - 414:04
COOL with Gray Code (G-COOL) - 514:12
COOL with Gray Code (G-COOL) - 614:17
COOL with Gray Code (G-COOL) - 714:20
COOL with Gray Code (G-COOL) - 814:23
COOL with Binary Encoding (9)14:30
Theoretical Analysis of G-COOL14:42
Demonstration of G-COOL15:21
Outline (6)15:37
Experimental Methods15:39
Results (Synthetic datasets) (1)15:56
Results (Synthetic datasets) (2)16:13
Results (Synthetic datasets) (3)16:23
Results (Synthetic datasets) (4)16:56
Results (Synthetic datasets) (5)17:10
Results (Synthetic datasets) (6)17:20
Results (Real datasets) (1)17:29
Results (Real datasets) (2)17:33
Results (Real datasets) (3)17:38
Outline (7)17:39
Conclusion17:41